[Assessment of Heavy Metal Pollution in Surface Dust of Lanzhou Schools Based on Random Forests]

In this study, seven types of heavy metal elements and 11 types of characteristic parameters affecting heavy metal pollution and accumulation in surface dust were selected. Based on the comprehensive pollution index (P_N) and potential ecological risk index (RI) calculated from the heavy metal element content of the school dust in the main urban area of Lanzhou City in 2018 as the training set, the P_N and RI of the information sampling points were estimated using random forests. Then, the temporal and spatial characteristics of heavy metals in school dust in the main urban area of Lanzhou were analyzed. Finally, the correlation coefficient was used to evaluate the advantages and disadvantages of the traditional interpolation results and the random forest interpolation results. The results showed that the concentrations of heavy metals in the dust were higher than the local background values. The over standard rate of a single sample is 100%, Zn is 5 times higher than the background value, and Pb is 4 times higher than background value. P_N in the study area was in the order Chengguan > Xigu > Anning > Qilihe, and RI was in the order Chengguan > Xigu > Qilihe > Anning. P_N and RI exhibited very similar spatial distribution characteristics, both located in transportation hubs or downtown. In winter and summer, P_N exhibited a high value, whereas RI had a high value. The reason for the high value of P_N and RI in winter was the increase of coal sources in winter. The comparison of spatial interpolation results shows that the correlation coefficient between the results of random forest interpolation and traffic flow and normalized building index is greater than that of the traditional algorithm.